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Author:
Department of Communications Engineering, Paderborn University
License:
MIT
Summary:
A collection of common functionality to simplify the design, training and evaluation of machine learning models based on pytorch with an emphasis on speech processing.
Latest version:
0.0.1
Required dependencies:
einops
|
ipython
|
lazy_dataset
|
natsort
|
paderbox
|
tensorboardx
|
torch
|
tqdm
Optional dependencies:
appdirs
|
codecarbon
|
coverage
|
humanize
|
matplotlib
|
mock
|
protobuf3_to_dict
|
pylint
|
pytest
|
pytest-cov
|
pyyaml
|
sacred
|
torch_complex
|
torchvision
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